Survey on QoE\QoS Correlation Models For Multimedia Services

TL;DR

This survey reviews existing models that attempt to predict user experience (QoE) from network quality parameters (QoS) in multimedia services, highlighting the challenges and techniques for reliable QoS/QoE correlation.

Contribution

It provides a comprehensive analysis of prior correlation models and optimization methods for accurately mapping QoS to QoE in multimedia applications.

Findings

Many models are partial solutions for QoS/QoE prediction

Optimization techniques can improve the reliability of correlation models

Predicting QoE from QoS remains a complex challenge

Abstract

This paper presents a brief review of some existing correlation models which attempt to map Quality of Service (QoS) to Quality of Experience (QoE) for multimedia services. The term QoS refers to deterministic network behaviour, so that data can be transported with a minimum of packet loss, delay and maximum bandwidth. QoE is a subjective measure that involves human dimensions; it ties together user perception, expectations, and experience of the application and network performance. The Holy Grail of subjective measurement is to predict it from the objective measurements; in other words predict QoE from a given set of QoS parameters or vice versa. Whilst there are many quality models for multimedia, most of them are only partial solutions to predicting QoE from a given QoS. This contribution analyses a number of previous attempts and optimisation techniquesthat can reliably compute the weighting coefficients for the QoS/QoE mapping.